Perforce's 2026 PHP Landscape Report Highlights a Growing Skills Gap with PHP
PHP continues to be a popular open source language for web applications and APIs, but fewer early-stage developers have PHP knowledge.
Systems | Development | Analytics | API | Testing
Modern Software Development For Today's Systems & Applications
EP20: The Agentic Enterprise
In this episode, *Dr. Sanjiva Weerawarana* and *Asanka Abeysinghe* are joined by WSO2 Chief AI Officer *Rania Khalaf* to discuss what the agentic enterprise really means. The conversation looks beyond AI pilots and explores the architectural foundations needed to make agents practical at enterprise scale. Topics include agents as first-class actors, the platform capabilities required to support them, and why identity, policy, observability, and audit matter in an agentic world. The episode closes with a practical view of what architects should start doing now.
How Focal Systems Closed the Inventory Gap with Data Streaming | Life Is But A Stream
The average grocery store has 65 to 80% inventory accuracy. One in 10 products is out of stock at any moment. For an industry operating on razor-thin margins and competing against digital-native challengers, that data gap is existential. In this episode, Kevin Johnson, CEO of Focal Systems, sits down with Joseph to explore how his team is using computer vision, data streaming, and stateful stream processing to close that gap at scale.
Healthcare Revenue Cycle Management Software: Architecture, Development Steps, Costs
let ‘s be real, the financial side of healthcare is a mess. For patients to schedule appointments and insurers to disburse the final reimbursement, the financial process must work seamlessly. When these systems work on a disconnected workflow, delays are bound to happen. To top it all, the sheer volume of patient data doesn't make the job easier. Its not about just losing money but also about losing patients’ valued time. It is important to have a centralised system.
Introducing Kong Agent Gateway: The Complete AI Gateway for Agent-to-Agent Communication
Kong Agent Gateway Is Here — And It Completes the AI Data Path You had a request going to a model, a response coming back, and a gateway in between to enforce policy. With the right solutions, this becomes manageable pretty quickly.. That world is over. Today's agentic architectures look nothing like that. Agents are delegating tasks to other agents via A2A. These other agents are producing and consuming event streams.
Govern the Full AI Data Path with Kong AI Gateway 3.14
The shift from single-model AI features to multi-agent pipelines is no longer a future concern — it's running in production today. MCP has become the de facto protocol for tool-calling, agent-to-agent (A2A) communication patterns are proliferating, and enterprise teams are wiring together complex AI workflows that span multiple providers, services, and agents. Every hop in that data path is an opportunity for something to go wrong. The challenge is governance.
Automate Document Extraction Across Any Layout or Format | Astera ReportMiner
Most enterprises spend 80% of analysts' time just extracting data from documents. Formats change. Vendors switch layouts. Templates break. Astera ReportMiner handles document variability automatically. It converts documents into structured, system-ready data regardless of layout without any manual effort. Teams get their time back. Data flows into downstream systems reliably. This video tells how ReportMiner handles real-world document variability and keeps your data pipeline moving automatically.
Your Customers Want AI Analytics. Tableau's Architecture Says No.
Tableau Next launched as a cloud-only platform on Salesforce Hyperforce. Every generative AI capability on Tableau’s roadmap runs through Salesforce Data Cloud. But for ISVs serving healthcare, financial services, or any customer operating under regulations like GDPR, HIPAA, or DORA, this locks them out completely.
How to give AI Agents secure access to systems (with remote MCP servers)
AI agents need access to your systems. But are you sure they're accessing them securely? In this video, Tun @DataSurfer breaks down the way most teams give AI agents access today: static API keys, shared credentials, no audit trail. It's a disaster waiting to happen, but what exactly can teams do about it?
Why your AI Agent needs both a key and a map
You asked Claude to generate a bitrise.yml. It came back clean: right steps, reasonable workflow names, valid YAML. You almost merged it. Then you noticed it’s using before_run instead of step bundles. There are no version locks on steps. The triggers are structured in a format Bitrise deprecated months ago. It’s a valid config, but it would never pass code review. The quality of an agent's interaction with your CI/CD comes down to two things: what it can do and what it knows.